Finding Profit in Your Organization’s Data: Examples and Best Practices

Introduction

Historically, the primary role of data in the industrial setting has been fault detection and diagnosis (FDD). Today, companies are increasingly looking to their data sets as assets to influence their revenue and profits. With the rise of big data storage and processing, combined with the new capabilities of machine learning for prediction and recommendation, these data sets may be converted from inactive, latent assets to critical-path components of an overall production ecosystem.

Presently the term data exhaust is used in many contexts and is perhaps a bit of a cliché; it’s worth taking a moment to define this term. Data exhaust is a by-product of industry: measurements taken and recorded without the requirement that they be used. Initially such measurements were taken for the purposes of FDD. But today, as the communication and computing capabilities of industrial systems advance, these data assets may now be leveraged to harness untapped potential.

When we add new, augmentable data assets—collected through new sensors and Internet of things (IoT) devices—the combined data set holds an expansive new role in industry. In this report, we explore a few real-world examples of how this is done today and the opportunities for the future.

A Data-Driven World

In their 2015 report, “What Is the Internet of Things?”,1 Mike Loukides and Jon Bruner describe the notion of frictionless manufacturing ...

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